This book introduces readers to copula-based statistical methods for analyzing survival data involving dependent censoring. Primarily focusing on likelihood-based methods performed under copula models, it is the first book solely devoted to the problem of dependent censoring. The book demonstrates the advantages of the copula-based methods in the context of medical research, especially with regard to cancer patients’ survival data. Needless to say, the statistical methods presented here can also be applied to many other branches of science, especially in reliability, where survival analysis plays an important role. The book can be used as a textbook for graduate coursework or a short course aimed at (bio-) statisticians. To deepen readers’ understanding of copula-based approaches, the book provides an accessible introduction to basic survival analysis and explains the mathematical foundations of copula-based survival models.
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This book introduces readers to copula-based statistical methods for analyzing survival data involving dependent censoring.
Chapter 1: Setting the scene.- Chapter 2: Introduction to survival analysis.- Chapter 3:  Copula models for dependent censoring.- Chapter 4: Gene selection under dependent censoring.- Chapter 5: The joint frailty-copula model for meta-analysis.- Chapter 6:High-dimensional covariates in the joint frailty-copula model.- Chapter 7:Dynamic prediction of time-to-death. Chapter 8: Future developments.- Appendix.
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The first book devoted to the problem of dependent censoring An essential textbook on survival analysis accessible to students, (bio-)statisticians, mathematicians, and medical researchers alike Written by leading statisticians in the field of survival analysis
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Produktdetaljer

ISBN
9789811071638
Publisert
2018-04-13
Utgiver
Vendor
Springer Verlag, Singapore
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet

Biographical note

Takeshi Emura, Chang Gung University

 Yi-Hau Chen, Institute of Statistical Science, Academia Sinica